Senior ML/AI Engineer

Summary

Build, train, and deploy machine learning models — with a focus on LLM fine-tuning and high-performance inference pipelines. You own models from experimentation through to reliable production serving.

Role Expectations

• •Train, fine-tune, and evaluate models — including LLMs via full fine-tuning, LoRA/PEFT, and instruction tuning.
• •Build and optimize inference pipelines for latency, throughput, and cost (batching, quantization, caching).
• •Design data pipelines and datasets for training and evaluation; ensure data quality and reproducibility.
• •Implement rigorous offline and online evaluation, benchmarking, and regression testing for models.
• •Partner with platform engineers to deploy models to production with monitoring and rollback.
• •Stay current with model architectures and translate research into practical improvements.

Required Skills

• •5+ years in ML/AI engineering; proven track record shipping models to production.
• •Strong Python and deep learning with PyTorch; solid understanding of the Transformer architecture.
• •Hands-on LLM fine-tuning experience (LoRA/PEFT, quantization, or full fine-tuning).
• •Experience building inference/serving pipelines and measuring model performance.
• •Comfortable with experiment tracking, versioning, and MLOps fundamentals.

Value adds:

• •Distributed training experience (multi-GPU, DeepSpeed, FSDP).
• •Publications, competition results, or notable open-source ML work.
• •Experience with retrieval, embeddings, and evaluation frameworks.

Core Stack:

Python · PyTorch · Transformers · LLM Fine-Tuning · MLOps · Prompt Engineering